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AI SEO or GEO building ideas

This is where it gets interesting.

What you’re describing sounds like a layer that sits above all of it:
  • Pulls in signals from every system (inventory, CRM, ads, comms)
  • Structures that into usable context
  • Pushes it back out so every platform is operating from the same intelligence
So the website, ads, BDC, etc. aren’t trying to figure things out independently, they’re all reading from the same source.
I'm taking a swing at solving for this right now with an open source project.

I think it goes beyond signals from inventory, CRM, ads, comms. Structure it. Push it back out so every platform reads from the same source instead of guessing on its own.

VCTRS.IO is my attempt at that. Three layers: what's declared, what's observed in the systems, and what's stuck in people's heads and never written down anywhere. That third layer is where it actually gets interesting. Most context plays stop at layer two. This industry has operated on gut for so long. That gut instinct or tacit layer might have to be a managed service.

Still early. Don't know what it becomes yet. The part I care most about is the open plugin layer. Dealers or anyone else can build their own and monetize it instead of guessing every use case for them. So far - beta users have come up with interesting things like creating employee schedulers, commission plan automations, employee onboarding, vendor digital rooms, or plug-ins as canaries in the coal mine so they dont have to have 30 windows open at a time.

Almost ready to open it up. It will be free. Bring your own keys and/or AI.
 
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✨ AI Highlights

  • GEO success requires topical authority across interconnected content, not isolated keywords
  • Structured inventory data and schema markup help AI surface specific vehicles
  • LLM.txt files alone are overhyped; foundational SEO practices remain essential

Dealers and vendors are debating how to adapt SEO strategy for an era where AI systems like ChatGPT answer questions directly rather than returning a list of links. Key discussion points include making inventory pages machine-readable with proper schema markup, earning citations through third-party sources rather than relying on first-party dealer sites, and one practitioner sharing a Chrome DevTools script to reverse-engineer how ChatGPT surfaces local dealership results. The emerging consensus is that foundational content quality and structured data matter more than quick-fix automation layers, and that AI-driven lead traffic — while still small — is already measurable and highly intent-driven.

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